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CECL Implementation Workshop

Brian J. Mischel, CPA Partner | BKD [email protected]

Andrew M. Wallace, CPA Senior Associate| [email protected]

May 29, 2019

Agenda for Today

What has changed over the last year

Refresher on the key principles of CECL & ASU 2016‐13

Potential regulator and audit expectations

Further understanding ofpossible CECL models

Where institutions are today & lessons learned from implementation efforts

What’s NextWhat’s next

What Has Changed Over the Last Year?

FASB Activity

6/18 –Transition Resource Group Meeting

11/18 –Transition Resource Group Meeting

11/18 –Finalized Timing Relief for Non‐PBE‘s

1/19 –Issues

Staff Q&A on WARM Method

4/19 –Finalized Fair Value Option for Eligible Assets

4/19 –Reverses Decision

on Vintage

Disclosure

4/19 –Rejects Regional Bank

Proposal

BKD's CECL Resource Center

Transition Resource Group (TRG)

• FASB has created a CECL TRG to solicit, analyze & discuss stakeholder issues of the new guidance

• Items discussed to date:‒ Transitioning PCI pools to PCD – Resolved‒ Consideration of prepayments for EIR in DCF – Resolved‒ Beneficial interests – Resolved ‒ Troubled debt restructurings – Resolved‒ Variable rate financial assets in a DCF – Resolved‒ Determining estimated life of credit cards – Resolved‒ Contractual Term: Extensions and Measurement Inputs ‐Resolved

‒ Vintage Disclosures for Revolving Loans ‐ Pending‒ Recoveries ‐ Pending

AICPA FINREC Credit Loss Whitepapers

ISSUE 1: Zero Credit Losses

ISSUE 2: Reversion Method: Estimation vs. Accounting Policy

ISSUE 6: Reasonable and Supportable Forecast

Note: See AICPA Credit Losses page for CECL Issues Tracker:CECL Issues Tracker

AICPA CECLGuidance: Identified Credit Loss Implementation IssuesTopics Covered:

Issue 1#: Zero Expected Credit Losses

Issue 2#: Determining the "Estimated Life" of a Credit Card Receivable

Issue 3#: Discounting Expected Cash Flows Using an Entity's Effective Interest Rate

Issue 4#: Transfer of Loans from Held for Sale to Loans Held for Investment and Transfer of Credit Impaired Debt Securities from Available‐for‐Sale (AFS) to Held‐to‐Maturity (HTM).

Issue #5: Scope of Purchased Financial Assets with Credit Deterioration Guidance for Beneficial Interests within Subtopic 325‐40

Issue #6: Reasonable & Supportable Forecasting

Issue #7: ‐Accounting for Troubled Debt Restructurings

Issue #8: Transition Guidance for Pools of Financial Assets Accounted for under Subtopic 310‐30

Issue #9: Auditing Accounting Estimates, including Fair Value Accounting Estimates and Related Disclosures

Issue #10: Auditing the new Credit Loss Standard

Issue #11: Simplifying Assumptions from Preparers

Issue #12: Collateral Maintenance Provisions

AICPA Agenda Topics


Issue #13: Consideration of Accrued Interest

Issue #14: Recoveries Issue #15: Discount Rates for Variable Rate Loans.

Issue #16: Accounting for Recoveries on Credit Insurance Contracts

Issue #17: Application of Subsequent Events

Issue #18: Review of ABA Discussion Paper: “Analyzing Current Loan Performance Under CECL. ”

Issue #19: Review of ABA Discussion Paper, “CECLEffective Date for Private Banks.”

Issue #20: Contractual Term: Extensions: Considering the Life

Issue #21: Inclusion of Future Advances of Taxes and Insurance Payments in Estimates

Issue #22: Reversion Method: Estimation vs Accounting Policy

Issue #23: Zero Expected Credit Loss Factors for Secured Financial Assets Secured by Collateral

Issue #24: Refinancing and Prepayments

Issue #25: Implementation Dates For Non‐PBEs

Issue #26: Capitalized Interest

Issue #27: Fair Value Option: Questions surrounding the one‐time election to apply the FVO upon adoption of the standard

Issue #28: Scope Exception for Loans and Receivables between Entities under Common Control

AICPA Agenda Topics


Issue #29: Gains and Losses on Subsequent Disposition of Leased Assets

Issue #30: Billed Operating Lease Receivables

Issue #31: Shorter Term Loans: Developing a Model for a 1‐year loan that has a 3‐Year Project Term

Issue #32: Partial Discounting: Issues included whether discounting certain inputs when using a method other than a DCFmethod in determining expected credit losses is acceptable

Issue #33: Accounting for Changes in FX Within Available for Sale Securities. Issue included

Issue #34: Zero Expected Credit Losses for Unsecuritized assets (including reinsurance receivables).

Issue #35: Application of 325‐40 for Trading Securities

Issue #36: Vintage Disclosures: Issues include whether entities should be required to make disclosures with respect to the presentation of revolving loans that have converted to term (and other potential required disclosures).

Issue #37: Subsequent Events Factors

Issue #38: Recognition of Subsequent Increases in Fair Value of Collateral for Collateral Dependent Loans

AICPA Agenda Topics

Bank Regulatory Guidance

ALERT! Joint Regulatory Agencies issue and finalize – Regulatory

Capital Rules – January 2019

Regulatory Capital Phase‐in

• Phase‐in the CECL Transitional amount by increasing its retained earnings by :

‒ 75 percent during the first year of the transition period, ‒ 50 percent during the second year of the transition period,

‒ 25 percent during the third year of the transition period.

ALERT! Joint Regulatory Agencies issue update – Frequently Asked Questions on the New Accounting Standard on Financial

Instruments –Credit Losses – April 2019

Bank Regulatory Guidance

Refresher on the Key Principles of CECL & ASU 2016‐13

• Financing receivables•Held to maturity debt (no more OTTI)

• Loan commitments, guarantees, standby L/C

• Lease receivables as lessor (ASC 842)

• Reinsurance receivables• Receivables on repurchase & securities lending agreements

Included

• Financial assets at fair value

•Available for sale debt (updated model)

• Participant loans defined contribution benefit plans

• Insurance policy loans•NFP pledges receivable

Excluded

CECL Scope

What is Included in ASU 2016‐13?

Topic 326 contains the following subtopics

Overall (326‐10) Measured at Amortized Cost (326‐20) ‐CECL

Available‐for‐Sale Debt Securities (326‐30)

• Record estimate of expected lifetime credit losses (of amortized cost basis) considering historical loss experience adjusted for:

• Contractual life considers expected prepayments but excludes– Expected extensions, renewals &modifications unless expected to

happen in a TDR

Historical lifetime

credit loss

Current conditions adjustment

Forecast adjustment

Current expected credit loss

CECL Key Highlights

CECL Key Highlights

• Collective Measurement: Measured on a collective pool basis based on similar risk characteristics unless the asset does not share similar risk characteristics

• Reversion: For future periods where forecasts are not supportable entity shall revert to historical loss information either

‒ Immediately‒ On a straight‐line basis ‒ Or using another rational & systematic basis

CECL Key Highlights

• Collateral‐dependent practical expedient remains:‒ Collateral‐dependent definition = foreclosure probable or repayment expected substantially through operation or sale of collateral when borrower is experiencing financial difficulty

‒ If collateral dependent shall not adjust value of collateral for expected future changes in value

• Record even if risk is remote: Include a measurement of expected risk of credit loss even if that risk is remote

‒ See AICPA whitepaper

• Troubled Debt Restructuring (TDR) guidance remains however must include impact of TDR concession in the allowance when reasonably expected– What is reasonably expected? (See OCC BAAS #12B)– Causes potential mismatch of allowance impact and actually TDR

and disclosure

• Principle based model selection: Does not prescribe a specific model or method to be used– FASB believes models do not need to be “unnecessarily

complex”

CECL Key Highlights

Purchased Assets with Credit Deterioration

• Modifies the definition of what were previously known as purchased credit‐impaired (PCI)

• Purchased Assets with Credit Deterioration (PCD): – “Acquired financial asset or acquired groups of financial assets

with similar risk characteristics that have experienced a more‐than‐insignificant deterioration in credit quality since origination, based on the buyer’s assessment.”


PCIPurchased Financial Assets with Credit Deterioration (PCD)

Acquired individual financial assets (or groups of financial assets with similar risk characteristics) that as of the date of acquisition have experienced a more‐than‐insignificant deterioration in credit quality since origination, as determined by an acquirer’s assessment. (emphasis added)ASU 2016‐13 Glossary


Some Factors for Assessment of PCD Assets (326‐20‐55‐59)

Financial assets that are delinquent as of the acquisition date

Financial assets that have been downgraded since origination

Financial assets that have been placed on nonaccrual status

Financial assets for which, after origination, credit spreads have widened beyond the threshold specified in its policy

Business Combinations: PCD vs. Non‐PCD

PCD Loans

(326‐20‐30‐13)

• Allowance added to the purchase price to determine the initial amortized cost basis

• “Gross Up”

Non‐PCD Loans

(326‐20‐30‐15 & 805‐20‐30‐4A)

• Allowance accounted for in a manner consistent with originated assets

• Not permitted to net any purchase discount with the allowance

• “Double Count”


• Purpose is to have consistency with originated assets

• Initial allowance for credit losses will be added to the purchase price rather than being recorded as a credit loss expense in the income statement

• Subsequent changes in the allowance for credit losses for PCD assets will be recorded through provision in the income statement

• Impacts more than just loans

• Non‐PCD purchased loans are not in this scope (see example)

PCD Example

Bank ABC pays $750,000 for a loan with an unpaid contractual balance of $1,000,000. The loan is measured at amortized cost basis. At purchase, the allowance for credit loss on the unpaid principal balance is estimated at $175,000.

Loan—par amount $ 1,000,000Loan—noncredit discount $ 75,000Allowance for loan losses $ 175,000Cash $ 750,000

$75,000 noncredit discount would be accreted into interest income over the loan’s life.

Non‐PCD Example

Using the same fact pattern as before except the loan is not considered PCD:Entry for acquisitionLoan—par amount $ 1,000,000Loan—credit & yield discount $ 250,000Cash $ 750,000

Entry for initial allowanceProvision expense $ 175,000Allowance for loan losses $ 175,000

Transition Accounting: Non‐PCD assets

• Recognize in retained earnings a cumulative‐effect adjustment for the changes in the allowances for credit losses on the balance sheet as of the beginning of the first reporting period in which new standard is adopted.

• Debt securities (AFS and HTM) which OTTI had been recognized prior to the effective date will transition prospectively with the previous effective interest rate locked in and amounts recognized in OCI related to cash flow improvements will continue to be accreted on a level‐yield basis over the remaining life.

Transition Accounting: PCI Loans

• Existing PCI loans‒ PCI loans will become PCD loans upon implementation of CECL

‒ Do not reassess whether previously acquired PCI loans meet the definition of PCD loans Do not move non‐PCI loans to PCD; keep pools of non‐PCI &PCI the same from previous acquisitions

If system (or manual tracking) has capabilities, will be beneficial to tag which loans are previously acquired PCI loans

Transition Accounting: PCI Loans

‒ Existing PCI loans ‒ Apply the new PCD asset gross‐up (amortized cost and allowance) at transition to all PCI loans now included as PCD

‒ Change in ALLL under CECL is an adjustment to the amortized cost basis It is not part of the cumulative‐effect one‐time adjustment

Transition Entry Required for PCI to PCDLoan is not on non‐accrual and management has not seen any decline in cash flow expectations since acquisition and therefore no allowance is recorded at 12/31/19 prior to CECL

Facts for PCI Loan at Transition

Principal balance at 12/31/19 $ 1,750

Nonaccretable discount at 12/31/19 500 (under current GAAP this reduces the carrying value of loan and is not included on the balance sheet)

Accretable discount at 12/31/19 200

CECL allowance at implementation 505 (Does not have to done using a DCF. Any method is allowable. Most institutions believe the current nonaccretable discount isthe floor for this at transition. Does not have to match nonaccretable)

General Ledger PCI PCD Transition Entry Debit Credit Principal balance $ 1,750 $ 1,750 Nonaccretable discount 500 Nonaccretable discount (500) ‐ Accretable discount 5 Accretable discount (200) (195) * Allowance (505)Loans 1,050 1,555 Gross up

Allowance (505)Net Loans $ 1,050 $ 1,050

* effective interest rate for accreting income will be lower given the 195 is applied to a larger grossed up loan balance

In summary: What happens to PCI assets at the Transition date? • PCI assets prior to effective date become PCD assets

• PCD assets as of the effective date will be required to be grossed up on the balance sheet by the amount of its allowance for expected credit losses as of the effective date.

• Subsequent changes will be recognized by charges or credits to earnings.

• Continue to accrete the noncredit discount or premium to interest income (based on effective interest rate after gross‐up for the CECL allowance at adoption)

PCD – other changes

• An entity must allocate the noncredit discount or premium resulting from the acquisition of a pool of PCD financial assets to each individual asset in the pool;

• When using a method to estimate the allowance for credit losses that discounts expected future cash flows, the discount rate used is the rate that equates the purchase price of the PCD asset with the present value of the estimated future cash flows at the acquisition date; and

• When using a method to estimate the allowance for credit losses other than one that discounts expected future cash flows, the allowance estimate is based on the unpaid principal balance (face or par value) of the PCD asset.

Available‐for‐Sale Securities

ASU 2016‐13 changed the model, but not technically CECL:• Will follow an allowance approach vs. direct

write‐off which will allow subsequent reversals

• Allowance would be limited to the amount which fair value is below amortized cost

• Length of time fair value is below cost should not be considered in determining any credit loss exists

Available‐for‐Sale Securities

Transition Accounting: OTTI Securities

• Debt securities (AFS and HTM) which OTTI had been recognized prior to the effective date will transition prospectively with the previous effective interest rate locked in and amounts recognized in OCI related to cash flow improvements will continue to be accreted on a level‐yield basis over the remaining life.

• Many existing disclosures have been carried forward without change

• Detailed credit risk attribution rollforward will likely be needed.‒ A discussion of risk characteristics relevant to each portfolio segment ‒ A discussion of the changes in the factors that influenced management’s

current estimate of expected credit losses and the reasons for those changes ‒

• For the estimate, will need to disclose‒ Description of how expected losses are developed‒ Factors that influenced the current estimate, including reversion methods

• PBE’s will add new vintage credit quality disclosure

Disclosures

New Disclosures – Credit Quality Vintage

• Not required for entities that aren’t public business entities (PBE) • For PBEs that are non‐SEC filers, transitional relief will allow banks to “build up” data over time to meet full disclosure requirements

ASU 2016‐13 Implementation Dates

Regulatory/ Auditor Expectations

Regulatory Expectations

• Joint Statement on the New Accounting Standard on Financial Instruments ‐Credit Losses (June 2016)

• Frequently Asked Questions on CECL (Updated September 2017)

• OCC Bank Accounting Advisory Series (BAAS), (August 2018)

• Capital Phase In

Formal Regulatory Guidance

Key Takeaways – Joint Statement

New standard will be scalable to all institutions

Smaller & less complex institutions will be able to adjust their existing allowance without the use of costly &/or complex modeling techniques

Inputs to allowance estimation methods currently used will need to change to properly implement CECL requirements

Won’t require institutions to engage third‐party vendors to assist in implementing & calculating allowances within CECL

Institutions may need to capture additional data & retain data longer to meet CECL data requirements

Key GuidanceInteragency CECLGuidance: Frequently Asked Questions on the New Accounting Standard on Financial Instruments –Credit Losses (last updated April 2019)

Topics Covered:Applicability of NewAccounting Standard

Background Collateral‐DependentFinancial Assets

Data

Debt Securities Effective Dates Implementation Methods

Off‐Balance‐SheetCredit Exposures

Public Business Entities Purchased Credit‐Deteriorated Financial Assets

Qualitative Factors

Reasonable and Supportable Forecasts

Regulatory Capital Regulatory Reports Segmentation

Supervisory Expectations

Third‐PartyVendors Troubled Debt Restructurings

Key GuidanceOCC Bank Accounting Advisory Series (BAAS), Topic 12D. Allowance for Credit Losses:Topics Covered:

What is meant by “lifetime” in the context of lifetime expected credit losses?

How should a bank measure lifetime expected credit losses?

When should a loan be charged off?

How should the bank determine the ACL on the loan?

When determining the ACL, is it appropriate to both include a loan in a pool of loans as wellas perform an individual assessment of expected credit losses?

Should the bank include the charge‐off from the classified loan in the historical loss rate forthe pass‐rated loan pool?

Does the bank need to supplement its historical loss experience with external (i.e., peer ormarket) data when determining its ACL?

Should the bank supplement its historical loss experience with external (i.e., peer or market)data or qualitative factors when determining its ACL?

Key GuidanceOCC Bank Accounting Advisory Series (BAAS), Topic 12D. Allowance for Credit Losses:Topics Covered:Will a bank be subject to criticism if its methodology is inappropriate but its ACL balance isappropriate?

Should the bank consider the borrower‐paid, individual PMI when determining the ACL?

Would the staff response to question 10 be different if the bank obtained mortgage insuranceon a pool of loans, rather than borrower‐paid PMI, and a loan would no longer be coveredunder the bank’s insurance policy if sold to another institution?

Is a bank’s reasonable and supportable forecast period expected to cover a specific amount oftime?

What information should a bank consider when developing or obtaining a reasonable andsupportable forecast?

Is the unfunded commitment associated with a HELOCunconditionally cancellable?

For these types of loans, what is the period of time over which a bank should measureexpected credit losses?

How should a bank, as lessor, determine the ACL on its portfolio of sales‐type or directfinancing leases?

• Regulators are asking about CECL

• For non‐SEC issuers focus is still in the planning & readiness areas that will be discussed later

• Model risk management and model validation guidance being followed if applicable

Regulatory Expectations

Model Validation

2006 Interagency policy Statement on ALLL: states that the the institution should periodically validate the ALLLmethodology. This validation process should include procedures for a review, by a party who is independent of the institution’s credit approval and ALLL estimation processes, of the ALLLmethodology and its application in order to confirm its effectiveness.

Supervisory Guidance on Model Risk Management:Depending on the complexity of the model, should consider the supervisory guidance as many elements in the guidance are necessary even if technically not considered applicable.

SEC Expectations

• SAB 74 Disclosures‒ Describe the effect of new accounting policies resulting from the adoption of the

standard and a comparison with the current accounting policies

‒ Describe reasonably estimable quantitative information, even if it lacks complete certainty or is only for a subset of the company’s arrangements

‒ Describe qualitative information on the impact of the standard on future financial statements, if its effect is unknown

‒ Describe progress toward implementing the standard, including significant outstanding items

‒ Be included in financial statement notes, if the change in accounting is pervasive or material.

Auditor Expectations: Documentation is the key

Overall to test the allowance, the auditor can apply one or a combination of the three approaches below 1) Test management’s process (most common)

Will evaluate the reasonableness of assumptions used by management that are significant to the ALL

Test and evaluate the completeness, accuracy and relevance of data used.

Evaluate the consistency of management’s assumptions with other information

2) Develop an independent estimate, which generally involves using management’s assumptions or alternate assumptions

3) Review subsequent events or transactions to provide evidence about the reasonableness of the allowance.

Internal Controls over Financial Reporting (ICFR)

• Controls over historical data not included in the current incurred ALLLmodel will need to be assessed as absent controls, more detailed test work will be necessary.

• Many of the governance controls related to the ALLL process will stay the same.

• As more data is required for the ALLLmodel under CECL, then controls specifically around the new data elements will be necessary if considered a key input.

IMPLEMENTATION – LESSONS LEARNED

Vision without action is a daydream. Action without vision is a nightmare.

FDIC Chief Accountant Robert Storch“The expectation is, except perhaps for the very shortest term loans, there need to be an increase,” Storch said. “There’s no real good way of forecasting that I know what the overall effect will be because it’s going to depend on the composition of each bank’s portfolio and the underwriting practices they use, what their allowance levels are going into the effective date, and also what the forecasts are for the credit risk drivers that are key factors in estimating collectability.”

CECL Readiness & Implementation Process

Create committee &

timelineEducation

Pool segmentation & credit risk identification

Data inventory & gap analysis

Planning & Readiness

Model(s) selection & development

Model(s) finalization & parallel run

Modify policies,

procedures, controls & disclosures

Implementation

CSBSCECL Readiness Tool

CSBSCECL Readiness Tool

The tool provides a framework that a financial institution could use to plan for the eventual implementation of these accounting changes. CECL will have a significant impact on the way a financial institution estimates and provides for credit losses and early preparation is prudent. The associated examiner guide provides talking points, limitations, and other information examiners might find helpful if the tool is encountered in an examination. As explained in the examiner guide, the tool is not intended to establish regulatory expectations or deadlines.

Where Are Banks Today?

Implementation –Where are Institutions Today?

Source: FDIC historical data

‐150.00%

‐100.00%

‐50.00%

0.00%

50.00%

100.00%

150.00%

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

Yr over Yr Change in ALLL & C/O Ratios

ALLL Change CO Change

2018 2017 2016

Net Charge‐off rate .08% .11% .11%

Allowance to Loans .32% .43% .44%

Source: National Banks: Peer Group Average Report


Create committee & timeline

66%

Education

83%

Pool segmentation

49%

Data Inventory and gap analysis

50%

Model(s) selection

47%

Model(s) finalization

8% Modify policies,

procedures, controls & disclosures

1%


Implementation

MODEL SELECTION

POOL SEGMENTATION

DATA INVENTORY

CECL – Data Inventory

MODEL SELECTION

POOL SEGMENTATION

DATA INVENTORY

2018 Survey: What do you believe will be your biggest obstacles to CECL implementation?

50%

50%

11%

10%

42% 49%

BIGGEST OBSTACLES

Data Inventory & Gap Analysis

Scalability of this process is driven off:• Institution’s pooling risk characteristics• Models being considered by an institution • Does the institution have an existing data warehouse and has it been audited

Four main areas of data gaps and issues• What you don’t have• What you do have• How you got it• How you will maintain it going forward


• Inability to access historic data after a certain time frame

• Lack of quality historic data from acquired institutions• Data points for future forecasts

What you don’t have:


• Accuracy and consistency of how data is input and recorded into loan systems

• Changes in underwriting or grading systems causing lack of consistency in historic data sets

What you do have:


• Validation of completeness & accuracy of data• Documented internal controls

How you got it:


• Maintained in‐house vs. vendor solution• Spreadsheet controls• Documented internal controls over changes

How you will maintain it going forward:


Peer data needed? Low level of losses – maybe

Data does not include full economic cycle – yes

Remaining contractual term exceed length of historical data ‐ yes


‐0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

3/14 6/14 9/14 12/14 3/15 6/15 9/15 12/15 3/16 6/16 9/16 12/16 3/17 6/17 9/17 12/17 3/18 6/18 9/18 12/18

Losses Perce

ntag

e

Period

Commerical and Industrial Loans Losses

Community Bank

PG

Chart using UBPR data for comparison


Consider having a rating system on Fields of data:• Client Determined Reliability Rating (High, Moderate ,Low)• Used in Current ALLL (Yes or No)• Control Testing Reliability Rating (High, Moderate, Low)

Items to Consider:• Duplicates?• Blanks or zeros• Maturity Date (ex. Any maturities prior to period end date)• Is TDR and Nonaccrual loans identified• How are deferred fees (FAS 91) accounted for in the system?• How valid are renewal dates?


• How to test historical data?‒ Public/ FDICIA/ or non‐public

Were there controls in place over the considered data fields If not, might need to pull loan files and agree to source documents

• Does the end of period balances reconcile to GL• Can you agree charge off/ recovery data to call report?

• Fields not covered take to source documentation


• After forming a complete list of known issues‒ Create a plan to address issues with data.‒ This will be helpful for examiners/ auditors in how you worked through the issues identified


CECL – Pool Segmentation

MODEL SELECTION

POOL SEGMENTATION

DATA INVENTORY

Pooling Segmentation & Risk Identification

ASC 326‐20‐30‐2:

“An entity shall measure expected credit losses of financial assets on a collective (pool) basis when similar risk characteristic(s) exist (as described in paragraph 326‐20‐55‐5).”

Aggregation of similar risk characteristics in ASC 326‐20‐55‐5 may include one or a combination of the following (not all

inclusive)

• Loan Type• Risk ratings or classifications• Collateral type • Size• Term• Geographical location• Industry of the borrower

Pooling Segmentation & Risk Identification

Pooling Segmentation

• Similar risk characteristics‒ What is the institution currently using?‒ To simplify consider federal call code as a start.‒ Does the institution have enough losses currently per considered segmentation.

‒ If peer loss data needs to be used, what level of disaggregation.

Pooling Segmentation

2018 Survey: Respondents were asked, “Do you believe you will need to modify current ALLL pooling segmentation for CECL?”

Yes – 63%

Example: Pool Segmentation & Risk Identification Process

Create a tool to filter amongst characteristics.


Results could look like this example


• Management determined the following risk characteristic worthy of additional consideration for CRE Owner Occupied:Collateral type – general purpose vs. special purpose


• Result: The charge‐offs based on collateral code do not result in identifiable differences over a year to year basis and total charge‐off counts did not warrant additional segmentation


• Start with what you are currently using for pooling under current ALLL practices.

• Analyze the loss data and see if the loss data shares similar risk characteristics.

• Biggest lesson learned: Don’t over complicate the process.

Pool Segmentation & Risk Identification Process

CECL – Model Selection

MODEL SELECTION

POOL SEGMENTATION

DATA INVENTORY

Specific model approach is not mandated; however, start by considering what is used currently

Institutions can leverage existing credit risk management systems & allowance methods

Model Selection

• Loss Rate Approaches snapshot and open pool approaches

• Vintage Analysis

• Lifetime PD & LGDAnalysis

• Discounted Cash Flow

• Weighted‐Average Remaining Maturity methodology (WARM)

Model Selection

• Selecting CECL models/methods may be challenging for institutions & includes difficult considerations such as

‒ Size & complexity of the institution ‒ Models/methods currently used‒ Leveraging models/methods in other areas (DFAST, loan pricing, ASU 2016‐01, etc.)

‒ Auditor/Regulator/Stakeholder expectations‒ Data limitations‒ Use of more than one model/method‒ Future growth plans of the institution‒ HTM securities & off balance sheet commitments

Model Selection

CECL Models

Open Pool Models ‐ Refresher

Loss Rate Models Under CECL Examples

• Segment at call code level • Sub‐segmented by risk rating

Cumulative (Cohort) loss rate models

• Vintage model (segment by year of origination)

Vintage loss rate models

Cumulative (Cohort) Loss Rate Models

• Freezes all the loans in a segment pool at a particular point in time, then tracks the loss history on those loans over the remaining lives

Call Code Segment Level Excel Example

Year Amortized CostLosses on Loans as of

December 31, 2013 Comments

2013 1,010,000$ -$ 2014 3,700 2015 7,600 2016 5,500 2017 1,650,000$ 3,900

20,700$ Cumulative lifetime losses on loans as of December 31, 20131,010,000$ Amortized cost balance as of December 31, 2013

a 2.05% Cumulative 4-year historical lifetime loss rateCurrent Conditions Q-Factor Adjustments

0.05% - Real estate value decreased0.03% - Unemployment rate increased

b 0.08% Total Current Q-Factor Rate AdjustmentForecast Q-Factor Adjustments (over 2 years)

0.04% - Expect additional real estate value decreases0.02% - Expect additional unemployment rate increases

c 0.06% Total Forecast Q-Factor Rate Adjustment

a+b+c 2.19% Total CECL Lifetime Loss Rate1,650,000$ Amortized cost balance as of December 31, 201736,126.83$ Allowance for expected credit losses at December 31, 2017

Pros Cons• Less complex model• Data collection less

complex (no origination data)

• Q factor adjustment process will be similar to current practice

• Overall process is familiar

• Assumes historical pool has same credit risk & terms as current pool

• May be reliant on older periods that are not relevant today

• Q factor & forecast adjustments are harder to support

Fields Needed‐ for Historical Periods

Loan # Book Balance Current Available Credit

TDR Status

Nonaccrual flag Unamortized Premium or Discount

Net Deferred Loan Fees or Costs

Fair value premium/ discount

GovernmentGuarantee

GuaranteedPercentage

Guaranteed Amount

Risk Rating by individual loan

Individual loan charge‐off

Individual loan recoveries

Individual loan segmentation

Vintage Loss Rate Models ‐Refresher

Vintage Loss Rate Models

• Considers the full life cycle of the loan pools. Vintage is the most commonly discussed, which is typically based on year of origination. However, analysis can be based on any type of shared pooling criterion & assets originated in a similar time period, i.e., loans originated from 2008 to 2013 based on FICO bands

Vintage Analysis Example

Pros Cons• Can be used to better isolate

pools by changes in economic conditions, collateral value & underwriting

• Improved ability to forecast as more historical data is collected

• Eliminates changes in portfolio growth

• Methodology can be leveraged in other models or assumptions (prepayment, PD/LGD)

• May require tracking of more loss pools

• If loan pools are not homogenous may become difficult

• May be reliant on older periods that are not relevant today

• Doesn’t work for non‐amortizing pools & possibly balloon loans

Fields Needed‐ for Historical Periods

Loan # Book Balance Current Available Credit

TDR Status

Nonaccrual flag Unamortized Premium or Discount

Net Deferred Loan Fees or Costs

Fair value premium/ discount

GovernmentGuarantee

GuaranteedPercentage

Guaranteed Amount

Risk Rating by individual loan

Individual loan charge‐off

Individual loan recoveries

Individual loan segmentation

Individual loan origination dates

Individual loan origination amounts

WARM Method

• The remaining life method utilizes average annual charge‐off rates and remaining life to estimate the allowance for credit losses (ACL).

• For amortizing assets, the remaining contractual life is adjusted by the expected scheduled payments and prepayments (i.e., paydowns).

• The average annual charge‐off rate is applied to the amortization adjusted remaining life to determine the unadjusted lifetime historical charge‐off rate.

WARM Method Example

WARM Key Assumptions

• Average annual net charge‐off rate:• Lookback period

• Amortization adjusted remaining life:• Paydowns (does not include charge‐offs)

• Contractual principal payments• Prepayments

•Qualitative adjustments:• Current conditions• Reasonable and supportable forecasts

Pros Cons• Better leverages current

processes including annualized historical loss rates and Q factor adjustments

• Less complex model• Easier to accumulate

historical loss rate data if pooling at call code

• Maybe difficult to accurately determine expected future payments

• Use of annualized loss rate may not align with lifetime loss experience

WARM

Other Models: DCF

Discounted Cash Flows (DCF): This method calculates the present value of expected future cash flows of a loan or loan pool discounted using its effective interest rate.

CECL allowance = Amortized Cost Basis – PV Expected Cash Flows

Although not required, this method most directly addresses the principles of the standard, & the key assumptions are discrete & transparent.

Vendors can provide the model but what about the assumptionsFor example – Looking at key decisions for Discounted Cash Flow (DCF).

Assumptions

Missing Maturity Information ability to select balloon vs. certain # of years

Option for use of book balance vs. amortized cost

Effective yield source Include prepayment and curtailment in effective yield

Option to manually enter PD/LGD Forecasting options

Prepayment Speed Curtailment rate

Recovery Loag

Other Models: DCF

• PD/LGD: is a component model that combines the probability that loans will experience a default with losses associated with those defaults as calculated based on exposure at default

• The PD component is a percentage of loans that have defaulted in a loan pool over a historical look‐back period (can be done on count or balance). The LGD component is the percentage of the defaulted loan balance (exposure at default) ultimately charged‐off

• The PD/LGD model can be used as a standalone orwithin the context of a DCF

Other Models: PD/LGD

Vendors can provide the model but what about the assumptionsFor example – Looking at key decisions for Probability of Default /Loss Given Default (PD/LGD).

Assumptions

Start date of most recent period Is the PD Count based or Dollar based

Length of each period Do I use a straight, weighted or custom average

Number of historical periods What economic factors will I tie into the model

Frequency to repeat historical periods How long do I forecast economic factors.

What are the default triggers?

Other Models: PD/LGD

Example: PD/LGD Model Using External Data

• As no specific models are required and institutions more than likely won’t have loss experience in HTM debt securities one solution may be to use external PD/LGD data from a bond accounting firm to create the CECL estimate or determination of materiality

• Probability of Default × Loss Given Default × Exposure at Default = Expected Loss (aka CECL allowance)

CECL allowance is the product of all three components

PD: what is the probability of a bond defaulting over the

contractual life of the bond?

Exposure at default: what is the outstanding balance at default?

Book value of your bond?

LGD: when the bond defaults, what

percentage of the exposure at default is

charged off?

Probability of Default & Loss Given Default Concept

• ASC 326‐20‐55‐6 lists some potentially highly judgmental decisions and one of them is the definition of default for default based statistics

• Therefore an institution first needs to define what is a default for their debt securities

PD ‐Defining a Bond Default

• A default is assumed to take place on the earliest of the following

‒ The date their rating is revised down to ‘D’

‒ The date a debt payment was missed;

‒ The date a distressed exchange offer was announced; or

‒ The date the debtor filed for, or was forced into, bankruptcy

Source: S&P 2016 Annual Global Corporate Default Study and Ratings Transitions, provided by Baker Group

PD ‐Defining a Bond Default

Municipal Probability of Default

• How do you model the probability of default of a municipal bond? Ratings Agencies such as S&P calculate the probability of a ratings move from one rating to another over a given time horizon (typically one year).

• Tables like the below could be used to create transition matrix or other PD models to determine the probability a debt security or pool of debt securities will default.

Source: S&P 2016 Annual U.S. Public Finance Default Study and Ratings Transitions

Example Municipal PD Transition Matrix

• An institution has a pool of A rated municipal bonds with $1,000,000 of amortized cost basis at December 31, 2018 and they all mature on December 31, 2022. There are no call features or expectations of prepayment

• Management believes the transition ratings table from 2016 are a good proxy for the potential rating movements for the remaining life, considering current conditions and reasonable and supportable future forecasts

• Management uses the ratings transition matrix from 2016 to estimate probability of default (i.e. rating transitions to D).

Example Municipal PD Transition Matrix

12/31/2018 12/31/2019 12/31/2020 12/31/2021 12/31/2022AAA ‐$ 87$ 256$ 501$ AA 18,600 36,138 52,688 68,319 A 1,000,000$ 962,200 927,329 895,082 865,194 BBB 18,600 34,432 47,893 59,324 BB 600 1,878 3,659 5,802 B ‐ 133 403 804 CCC/C ‐ 3 18 49 D ‐ ‐ 1 6

1,000,000$ 1,000,000$ 1,000,000$ 1,000,000$ 1,000,000$

Probability of Default 0.001%

Additional Probability of Default Considerations

• Pooling would need to go beyond security type (muni, corporate, MBS, etc.) and other risk factors (types of muni bonds) to also include ratings unless PD calculations are done on each security and then pooled up (bottom up vs. top down)

• Would “A” rated debt securities or pools of securities have enough time to transition to a default rating? Estimated PD = 0 or close to 0

• Trying to do this internally may be time consuming but could be done

• This is just one piece of the estimate as you still need to determine LGD, however could base materiality determination at this level

• From 1986–2016, the occurrence of defaults in the municipal/public finance sector was very rare

• 15 U.S. rated bonds defaulted in 2016; 13 of the defaults were issues within Puerto Rico

• The data includes the following types of municipal bonds: general obligation, lease obligation, water & sewer revenue, public power, airports, ports, toll roads & bridges, etc.

Source: S&P 2016 Annual U.S. Public Finance Default Study and Ratings Transitions, provided by Baker Group

Municipal Defaults Are Rare

Compare Municipal Bond Matrix vs. Corporate Matrix

Source: S&P 2016 Annual U.S. Public Finance Default Study and Ratings Transitions, provided by Baker Group

Municipal vs. Corporates

• A municipal expected loss model must also consider recovery rates of municipal defaults

• Recovery rates: the value creditors actually receive at the resolution of the default relative to what they should have contractually received (par value)

• Average recoveries on individual Moody’s‐rated municipal bonds since 1970 have been about 66% & are somewhat higher than the average 53% recovery rate for senior secured debt of global corporate issuers over a similar period

• Therefore in our example a potential estimate of CECL reserve on the $1,000,000 portfolio would be $4 ($1,000,000 X .001% X 66%)

Loss Given Default Concept

• Callable bonds: bonds that can be redeemed or paid off by the issuer prior to the bonds’ maturity date

• When an issuer calls its bonds, it pays investors the call price (usually the par value of the bond) together with accrued interest to date &, at that point, stops making interest payments

• Market rates down = more bonds called• Market rates up = less bonds called• What is the life of a callable bond?

Determining CECL Life of Munis

• What about nonrated securities? Many municipalities choose not to get a bond issue rated

• Institutions are already likely using third‐party municipal credit analysis as a part of their municipal credit program

• Nonrated securities need to be pooled together based on municipal credit metrics & related back to a Moody’s &/or S&P rating

• From there, the security will then go through the same probability of default & loss given default model as their rated counterparts

Nonrated Municipal Securities

Qualitative Factor Considerations and Incorporating Reasonable and Supportable Forecasts

Can you give an example of a qualitative adjustment for current conditions?

• Adjustments for current conditions continue to be critical under CECL.

• Adjustments to historical data or charge‐offs rates bridge the gap between loans in the current portfolio as of the reporting date and loans in historical data sets.

• Example:– The bank’s historical losses reflect loans originated under stricter

underwriting standards.– Loans in the bank’s current portfolio reflect loosened underwriting

standards when compared with the historical periods used for the WARM lifetime historical loss rate.

Can you give an example of a qualitative adjustment for reasonable and supportable forecasts?

• Focus on the factors relevant to collectability• Adjustments do not have to be macroeconomic in nature.• Acceptable to forecast specific events (e.g., factory closure)even if other

forward‐looking information is only reasonable and supportable for a shorter period of time

• Example:– The bank hears that a company may close a large factory within its footprint. The

factory employs a significant number of the bank’s borrowers.– Later, the company announces it will close the factory in three months. – The bank estimates that almost all losses related to the closure will be realized within

two years.

Examples of Qualitative Factors in the Standard

• The borrower’s financial condition, credit rating, credit score, asset quality, or business prospects

• The borrower’s ability to make scheduled interest or principal payments

• The remaining payment terms of the financial asset(s)• The remaining time to maturity and the timing and extent of

prepayments on the financial asset(s)• The nature and volume of the entity’s financial asset(s)• The volume and severity of past due financial asset(s) and the

volume and severity of adversely classified or rated financial asset(s)

• The value of underlying collateral on financial assets in which the collateral‐dependent practical expedient has not been utilized

• The entity’s lending policies and procedures, including changes in lending strategies, underwriting standards, collection, writeoff, and recovery practices, as well as knowledge of the borrower’s operations or the borrower’s standing in the community

• The quality of the entity’s credit review system• The experience, ability, and depth of the entity’s management, lending staff,

and other relevant staff• The environmental factors of a borrower and the areas in which the entity’s

credit is concentrated, such as:• Regulatory, legal, or technological environment to which the entity has

exposure• Changes and expected changes in the general market condition of

either the geographical area or the industry to which the entity has exposure

• Changes and expected changes in international, national, regional, and local economic and business conditions and developments in which the entity operates, including the condition and expected condition of various market segments.

Examples of Qualitative Factors in the Standard


Standard allows an entity to revert to historical loss information, with a straightline or immediate reversion both being acceptable methods if the expected contractual term of financial assets goes beyond periods for which reasonable and supportable forecasts can be obtained.


For accounting purposes, as confirmed by the AICPA’s Depository Institutions Expert Panel, changes to the length of the R&S forecast are considered a change in estimate and not a change in accounting principle. This also means that the R&S length is a key assumption in the estimate and not an accounting policy election.


• All forecasting models have limitations

• The longer the forecast the more volatility and risk of error

• Economy is exposed to exogenous external shocks which are difficult to predict


Many different methods to incorporate reasonable and supportable forecast adjustments.

• Topside• Reversion• Use of correlation

Download the free FRED Excel add‐in at https://research.stlouisfed.org/fred‐addin/

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